Comparison of Stock Price Prediction Models using Pre-trained Neural Networks
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Efficient Two Stage Identification for Face mask detection using Multiclass Deep Learning Approach
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Design an Adaptive Hybrid Approach for Genetic Algorithm to Detect Effective Malware Detection in Android Division
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Blockchain Framework for Communication between Vehicle through IoT Devices and Sensors
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Gas Leakage Detection in Pipeline by SVM classifier with Automatic Eddy Current based Defect Recognition Method
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A Review on Data Securing Techniques using Internet of Medical Things
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Machine Learning Algorithms Performance Analysis for VLSI IC Design
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Maximizing the Prediction Accuracy in Tweet Sentiment Extraction using Tensor Flow based Deep Neural Networks
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Assimilation of IoT sensors for Data Visualization in a Smart Campus Environment
Volume-3 | Issue-4
DDOS ATTACK DETECTION IN TELECOMMUNICATION NETWORK USING MACHINE LEARNING
Volume-1 | Issue-1
Gas Leakage Detection in Pipeline by SVM classifier with Automatic Eddy Current based Defect Recognition Method
Volume-3 | Issue-3
Design an Adaptive Hybrid Approach for Genetic Algorithm to Detect Effective Malware Detection in Android Division
Volume-3 | Issue-2
Comparison of Stock Price Prediction Models using Pre-trained Neural Networks
Volume-3 | Issue-2
Construction of a Framework for Selecting an Effective Learning Procedure in the School-Level Sector of Online Teaching Informatics
Volume-3 | Issue-4
Machine Learning Algorithms Performance Analysis for VLSI IC Design
Volume-3 | Issue-2
Efficient Two Stage Identification for Face mask detection using Multiclass Deep Learning Approach
Volume-3 | Issue-2
Characterizing WDT subsystem of a Wi-Fi controller in an Automobile based on MIPS32 CPU platform across PVT
Volume-2 | Issue-4
Assimilation of IoT sensors for Data Visualization in a Smart Campus Environment
Volume-3 | Issue-4
Design of Data Mining Techniques for Online Blood Bank Management by CNN Model
Volume-3 | Issue-3
Ethereum and IOTA based Battery Management System with Internet of Vehicles
Volume-3 | Issue-3
Volume - 5 | Issue - 2 | june 2023
Published
28 June, 2023
To choose the best forecasting model, it is essential to comprehend time series data since external influences like social, economic, and political events may affect the way the data behave. This study considers outside variables that could have an impact on the target variable used in improving the predictions. India Machinery and Transport Equipment Dataset is gathered from various sources, are cleaned, pre-processed, the missing values are removed, data types are converted, and dependent variables are identified before being used. By incorporating the SARIMAX model with the GARCH model and experimenting with various parameters and conditions, the current study seeks to enhance it. The SARIMAX-GARCH Model is a time series forecasting method used to predict market swings and export values. A helper model is developed to forecast the exogenous value to forecast the export value, which is then used as input for the final model. The ideal parameters for boosting the hybrid model's performance were identified through hyperparameter tuning. The results of this study provide estimates for future export values and contribute to a better understanding of India's Machinery and Transport Equipment export market. This research work focuses on export value forecasting with the use of future exogenous variables. Exogenous factors are essential for predicting market changes and, as a result, support the forecasting of precise export values.
KeywordsTime Series Forecasting SARIMAX External Factors Export Prediction GARCH ARCH Hybrid Forecasting model Exogenous variable Export Forecasting India Machinery and Transport export
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